计算机应用与软件2012，Vol.29Issue(12)：65-68,4.DOI:10.3969/j.issn.1000-386x.2012.12.019
基于人工蜂群和最近邻原则的无监督聚类方法
UNSUPERVISED CLUSTERING APPROACH BASED ON ARTIFICIAL BEE COLONY AND NEAREST NEIGHBOUR PRINCIPLE
摘要
Abstract
For the clustering partition issue, an unsupervised clustering approach based on improved artificial bee colony and nearest neighbour principle is given. This approach views every honey source as a candidate solution for the clustering, and designs a multidimensional code structure for the bee. To cluster effectively, based on better clustering centre selected by the employed bee and the onlookers in their local search phase, this approach divides all data patterns in clustering space by using the nearest neighbour principle in k-means. To improve local and global search ability of bee, the approach presents new local and global search method according to the feature of clustering problems. Simulative experimental results show that the new approach is feasible and effective.关键词
无监督聚类/人工蜂群/最近邻/k均值/粒子群优化Key words
Unsupervised clustering/Artificial bee colony/Nearest neighbour/k-means/Particle swarm optimisation分类
信息技术与安全科学引用本文复制引用
亓民勇,董金新..基于人工蜂群和最近邻原则的无监督聚类方法[J].计算机应用与软件,2012,29(12):65-68,4.基金项目
目家自然科学基金项目(61104179) （61104179）
山东省高校智能信息处理与网络安全重点实验室(聊城大学)资助 （聊城大学）
聊城大学科研基金项目(X09034). （X09034）
